The International Journal of Psychosocial Rehabilitation

Social Support And Quality of Life Among Psychiatric Patients In Residential Homes

Dan Sharir, Ph.D.1

Mihaela Tanasescu, MD, ScD.
Associate Professor of Health Sciences 2

David Turbow, Ph.D.

 Assistant Professor of Health Sciences 3

Yair Maman, Ph.D
 Professor of Psychology and Chair, Mental Health Counseling M.S. Program4

1,2,3 Touro University International, Cypress, California  4 Touro College, New York, New York

Sharir D., Tanasescu M., Turbow D. & Maman Y. (2007) Social Support And Quality of Life Among Psychiatric
Patients In Residential Homes. 
International Journal of Psychosocial Rehabilitation. 11 (1) 85- .

Dan Sharir, 360 Central Park West, Apartment 15D, New York, N.Y. 10025 USA
Email: or  

We examined the relationship between social support (SS) and Quality of life (QOL) among 83 patients suffering from schizophrenia, schizoaffective disorder, bipolar disorder, depression, and other psychiatric conditions from three residential facilities. When controlled for age, gender, type of funding, marital status, residence location, and length of stay, total SS was significantly related to total QOL and QOL subcomponents of finance and self and home maintenance. SS from friends was significantly related to the QOL subcomponent of housing. SS from a significant other was related to the QOL subcomponents of mental situation and services.

Keywords: Quality of Life (QOL), Social Support (SS), Residential Home Clients

The issue of quality of life (QOL) has received increased attention from the medical community due to its importance for patient rehabilitation (Lustig & Crowder, 2000).  QOL is known to be indicative of the level of social functioning in mental health patients (Menlowics & Stein, 2000).  In an era of deinstitutionalization, the proliferation of community support programs has played a pivotal role in providing basic support structures to patients with mental illness (Jinnett et al., 2001).   However, the maximum level of QOL attainable to patients with chronic mental illness is a topic for continued discussion.

QOL can be defined as an overall sense of well-being, comprised of both objective and subjective evaluations of physical, material, social and emotional well-being together with personal development and purposeful activity (Felce & Perry, 1996). Measurement of QOL can be a comprehensive means of evaluating various aspects of care through the exploration of subjective judgments of persons with severe mental illness (SMI) of their own welfare and by objective assessments of their life circumstances by researchers (Clarkson & McCrone, 2000).  The subjective QOL refers to the level of satisfaction of a person with his or her living situation and general well-being, while objective pertains to how well the patient functions in social settings and in daily activities (Mares, Young, McGuire, & Rosenheck, 2002). The level of satisfaction with interpersonal relationships and subjective QOL of patients with SMI may be lower than for people from the general population (Tempier, Caron, Mercier & Leouffre, 1998).  

QOL derives in large part from social contact (Bigelow et al., 1991). Social contact fulfills the personal needs of mentally ill individuals for affection and promotes self-esteem.  Social contact also contributes to a sense of affiliation in people with mental illness (Corrigan, 2003).  Patients with SMI who have access to community support services report having acceptable levels of satisfaction with their lives (Trauer et al., 1998).  Unfortunately, many activities that can potentially fulfill basic personal needs for social contact are unavailable to people with mental illness in mental health settings.  Also, people with mental illness tend to have small, low-density social networks comprised mainly of family members (Brunt & Hansson, 2002).   This lack of social networks in mentally ill patients may contribute to the onset of psychopathological symptoms, which can in turn place a burden on psychiatric services and in-patient services.   

Previous research has demonstrated that heightened social support can improve the QOL of persons with mental illness (see for example, Yanos et al., 2001; Nelson et al., 1995).  Social support acts to buffer the impact of stressful experiences, such as those related to physical health (Swindells et al., 1999).  Social support can also moderate the effects of pain, certain functional limitations, and depression (Blixen & Kippes, 1999).  

It has previously been shown that the quantity of supportive social relationships is predictive of subjective QOL in persons diagnosed with severe mental illness (Baker et al. 1992; Bengtsson-Tops & Hannson, 2001; Caon et al. 1998; Hannson et al., 2002; Lam & Rosencheck 2000; Rudnick & Kravetz, 2001). Especially when present within a context of large network size (Goldberg et al., 2003), social support can promote recovery in people with serious mental illness (Corrigan and Phelan, 2004). Mares, Young, McGuire & Rosenheck (2002) found that a desirable social climate was positively associated with subjective QOL in mental health patients. Previous researchers have used the Bigelow Quality of Life Questionnaire (Bigelow et al, 1991) to individually measure various components of QOL in mental health patients (Baker et al., 1992; Caron et al., 1998; Goldberg et al., 2003; Mares et al., 2002; Nelson et al., 1995; Skinner et al., 1999 and Yanos et al., 2001).  Our study was unique in that we assessed all domains of the Bigelow questionnaire, both subjective and objective, and also assessed the relationship between total quality of life (TQOL) and its individual subcomponents to social support.  We also used multivariate models to assess the possible role of age and other variables as potential predictors of QOL and its subcomponents due to their known correlation with satisfaction (Chand et al., 2004; Blenkiron & Hammill, 2003; Clarkson & McCcCrone, 2000; and Mercier et al., 1998).

Study Population and Sampling
Convenience sampling was used to select subjects for the study. Participants were recruited through personal appeal, and indirectly through the residential manager at each facility. The study participants resided at three separate residential facilities
Potential participants were informed of the nature of the study, the survey method and the anticipated amount of time required for participation. Patients were informed that their participation was strictly voluntary and that there were no penalties for non-participation. Any confidentiality concerns were also addressed. Patients were also encouraged to discuss any concerns about the objectives of the study.

Data collection
The modified Quality Of Life Questionnaire Interviewer Rating Version questionnaire was administered to assess QOL.  The Multidimensional Scale of Perceived Social Support (MSPSS) was administered to assess social support. Demographic and funding information, as well as information on patients’ diagnosis was also collected.

The QOL components assessed in the Bigelow questionnaire are: self and home maintenance ability, financial situation, availability of employment and transportation, available services, physical condition, meaningful use of time, and ability to complete tasks. Acronyms used for the nine subcomponents of QOL are listed in Table1.

Table 1. Acronyms used for QOL and its nine subcomponents

TQOL = Total QOL

QOLE = QOL subcomponent of employment

QOLF = QOL subcomponent of finance

QOLPH = QOL subcomponent of patient health and services

 QOLH = QOL subcomponent of housing

QOLSH = QOL subcomponent of self and home maintenance

QOLM = QOL subcomponent of mental situation and services

QOLT = QOL subcomponent of ability to complete tasks

QOLU = QOL subcomponent of patient use of time

QOLTR = QOL subcomponent of transportation services

For the modified Bigelow QOL questionnaire, a total QOL score was calculated as a sum of the scores on the individual items. Total scores were then projected onto a range of 0 – 212 with the high end representing better quality of life. Subjective and objective domains were reported both separately as subjective QOL and objective QOL scores and together as part of a total score for each of the patients. Not all sections had an equal number of questions, for example twelve questions were asked in the mental health section and only 2 questions were asked in the transportation section. Reliability and validity of the QOL Interview (interviewer rating version) was previously assessed (Bigelow et al., 1990). Fifty-six items had Cronbach’s Alpha greater than .70 and more than half the items were above .80. According to the authors of the study the questionnaire demonstrated good face validity in its credibility and acceptance among experienced practitioners. The interview is readily administered and easily scored and was used successfully in several program evaluations (Bigelow et al., 1990).

The MSPSS questionnaire is comprised of 12 items rated on a 7-point Likert-type scale (response format ranges from, 1 = very strongly disagree to 7 = very strongly agree). A higher score signifies increased levels of perceived social support. The score on individual items on the MSPSS were summed and divided by 12. Scores on the four items that comprise each subscale were also summed and divided by 4 (Cecil, Stanley, Carrion, & Swann, 1995).

Canty-Mitchell & Zimet (2000) assessed the reliability and validity of the MSPSS instrument. The Cronbach’s Alpha coefficient was .93; the The Cronbach’s Alpha coefficient of the three subscales of family, friends and significant other were .91, .89 and .91 respectively. Correlation coefficients were used to assess the validity of the MSPSS instrument by comparing it to the Adolescent Family Caring Scale (AFCS). The results showed that for the family subscale the correlation was .76, for the friends’ subscale it was .33, and for the significant other subscale was .48 (Canty-Mitchell & Zimet, 2000).

In attempting to assess QOL of people with mental illness there is a concern regarding the validity of self-reported ratings by patients. Limitations on the validity of self-reported QOL  may be partially attributatble the psychopathology of the patients, which can distort mental, emotional and social judgments (Atkinson, Zibin, & Chuang, 1997). Two safeguards were utilized to minimize any potential bias of patient’s self-reported ratings. First, eleven questions from the survey instruments were answered directly by the interviewer in order to offset any response bias on the part of the patient. Secondly, the questionnaire included both objective and subjective criteria .

This study was approved by the Touro University International institutional review board.

Statistical analyses
All statistical analyses were performed using the SPSS Graduate Pack 13.0 for Windows program.
Total SS and support of friends, family and significant other, together with age, gender, residence location, type of funding, marital status, and length of stay were examined for their relationship to QOL and its subcomponents via multiple regressions and MANCOVA.

Data was collected on 83 psychiatric patients, 61 men and 18 women (Table 2). The mean age of respondents was 38 years with a range of 20 to 57 years. The average length of stay at the residential facility was 55.5 months (4.6 years). Fifty-nine of the study participants were Caucasian (71.1%), eight were Hispanic, seven were African American, seven were Jewish American, and two were Asian. Sixty-seven patients received Medicaid financial support and 16 received Medicare financial support. Sixty-nine patients were single, nine were divorced and five married. Among members of the study population, 38 patients had been diagnosed with Schizophrenia or schizoaffective disorder, 22 patients had bi-polar disorder, 18 had depression disorder and five patients diagnosed with other psychiatric conditions (Table 2b).

Table 2a. Characteristics of study participants (N=83)   ____________________                                                                                        
Variables                                                                                     N = 83         % 
            Male                                                                                    65         78.3
            Female                                                                                18          21.7
            Caucasian                                                                            59          71.1
            Hispanic                                                                                8            9.6
            African American                                                                  7            8.4
            Jewish American                                                                   7            8.4
            Asian                                                                                    2            2.4
Marital status
            Single                                                                                   69         83.1
            Divorced                                                                               9           6.0
            Married                                                                                 5         10.8
Residence location
            LOCATION1                                                                     26          31.3
            LOCATION2                                                                     23          27.7
            LOCATION3                                                                     34          41.0
           Medicaid                                                                              67          80.7
           Medicare                                                                              16          19.3

Table 2b. Characteristics of study participants (N=83) contd._________________                                                                                         
Variables                                                                                     N = 83         % 
Psychiatric conditions
             Schizophrenia/schizoaffective disorder                                 38          45.2
             Bipolar disorder                                                                 22          26.2
             Depression                                                                         18          21.4
             Other psychiatric conditions (Personality disorder,
             ADD/ADHD, anxiety, panic, impulse control disorder
             and obsessive compulsive disorder)                                      5             6.0

Study participants scored highest on QOLM and lowest on QOLE. Participants tended to report low scores on QOLTR (Table 3).

Table 3. Descriptive statistics – QOL and subcomponents (N = 83)
Variable       Mean   SD  # Questions  Mean divided by
                                                            # questions asked 
TQOL          159.9     15.6          56                2.9
QOLM          42.9       4.6           12                3.6
QOLE           14.1       7.5             9                1.6
QOLH          26.9        2.0            8                 3.4
QOLSH        18.4        2.2            7                 2.6
QOLU          18.8        3.4            6                 3.1
QOLT          16.3        3.0            5                 3.3
QOLPH       12.3        1.7            4                 3.1
QOLF            7.0        0.9            3                 2.3
QOLTR         3.3        1.6             2                1.7
QOLsub      55.45      7.58          17               3.3
QOLobj      106.0      9.67          39               2.7                     

Subjects reported having more social support from friends than from family or from significant other.  This is evidenced by the fact that the mean scores on the ‘friends’ subcomponent of social support were significantly higher than the mean scores of  the ‘family’ and ‘significant other’ subcomponents (Table 4).

Table 4. 
Descriptive statistics – Social support and subcomponents (N = 83)                       
Variable                                                                     Mean       SD     # Questions 
Total social support                                                    69.6      14.7          12
Social support subcomponent family                           21.3        8.3            4
Social support subcomponent friends                          26.4        2.9            4
Social support subcomponent significant other             21.9        7.4            4        

Table 5

Results of multiple linear regression using total social support as the main predictor and TQOL and subcomponents as dependent variables (N = 83)        


Total SS                     .300*     .101      .017*      .024      .023    .040*      .059     .022      .024    -.011

Residence Location

Location 3 (reference)

Location 1                5.858    –2.821     .664**  .860        .784  1.494*     .739     1.398  1.803     .936

Location 2              14.128** 3.686*  .964**   .180        .087  1.563** 2.987**    .574  3.552** .536

Funding                    5.491     6.659*   .330      .679        1.263   .278      -.515   –2.795* -.551     .144

Gender                   –2.470       -.340      .494     .410        -.663  –1.378    -.558      .142   -.626      .048

Age                          -.040       -.310**   .040*    .004       .017    -.018       .125       .004    .118*   -.021

Length of stay         .201*      .114** -.005      .001        .028*   .012       .031      .015   -.016      .021*

Marital Status

Single (reference)

Married                   -6.067       5.179   -.895* –1.309     -.649 –1.292   –1.876  –2.144  –3.121*  .042

Divorced                –7.262       1.036   -.466     –1.293* -.892 –1.064   –1.290  –1.357  –2.141     .206

<>**p ≤ .01,*p .05, beta coefficients are reported
Funding (Medicaid vs. Medicare), Gender (Men vs. Women), Length of stay (months), Age (years), Location 3 is used as a reference, Single status is used as a reference, total social support represents a score made up of family, friends and significant other. The coefficients are the un-standardized coefficients.

Ten multiple regression procedures were performed on TQOL and its subcomponents (QOLE, QOLF, QOLPH, QOLH, QOLSH, QOLM, QOLT, QOLU, and QOLTR) with total social support as a main predictor of both TQOL and its subcomponents (Table 5). Total social support was significantly related to TQOL (B = .300, p ≤ .05). Other significant predictors of TQOL were location 2 (B = 14.128, p ≤ .01) and length of stay (B = .201, p ≤ .05). Significant predictors of QOLE included location 2 (B = 3.686, p ≤ .05), type of funding (B = 6.659, p ≤ .05), age (B = -.310, p ≤ .01) and length of stay (B = .114, p ≤ .01). Total social support was significantly related to QOLF (B = .017, p ≤ .05). Other significant predictors of QOLF were location 1 (B = .664, p ≤ .01), location 2 (B = .964, p ≤ .01), age (B = .040, p ≤ .05), and married status (B = -.895, p ≤ .05). Using QOLPH as the dependent variable divorced status was a significant negative predictor (B = –1.293, p ≤ .05). Using QOLH as the dependent variable length of stay was a significant positive predictor (B = .028, p ≤ .05). Using QOLSH as the dependent variable total social support was a significant positive predictor (B = .040, p ≤ .05). Using QOLM as the dependent variable residence location 2 was again a significant predictor (B = 2.987, p ≤ .01). Using QOLT as the dependent variable, type of funding was a significant predictor (B = –2.795, p ≤ .05) with Medicaid patients exhibiting greater QOLT than Medicare patients. Using QOLU as the dependent variable significant predictors were location, with location 2 having significantly higher QOLU than location 3 (B = 3.552, p ≤ .01), age (B = .118, p ≤ .05), and marital status, married patients having lower QOLU (B = –3.121, p ≤ .05). Using QOLTR as the dependent variable, only length of stay was a significant predictor (B = .021, p ≤ .05). The R2 coefficients for predicting QOL and its subcomponents were respectively TQOL – .304**, QOLE – .350**, QOLF – .327**, QOLPH –  .116, QOLH – .230*, QOLSH – .377**, QOLM – .359**, QOLT – .356**, QOLU – .284, and QOLTR – .102 (**p ≤ .01, *p ≤ .05). A MANCOVA analysis was also performed (data not shown). Thus, taking into account all TQOL components as dependent variables at the same time, results were consistent with the results of the linear regression analyses.

When objective QOL and subjective QOL were used as the dependent variable respectively, a significant positive relationship emerged between total social support and objective QOL (B = .176, p ≤ .05) and between total social support and subjective QOL (B = .140, p ≤ .05). Longer length of stay was associated with higher objective QOL (B = .176, p ≤ .01), however, length of stay was not significantly related to subjective QOL.

Linear regressions were also performed using the three subcomponents of social support (family, friends, and significant other) as independent variables of TQOL and its subcomponents. Social support from friends was related to QOLH (B= .228, p ≤ .05) and tended towards positive association with QOLF (B = .075, p= .075). Social support from family tended to be associated with QOLSH but did not reach significance (B= .062, p= .059). Social support from family was not significantly related to other components of quality of life. Social support from a significant other was associated with QOLM (B= .153, p ≤ .05).

This study was focused on the relationship of social support and other potential predictors to QOL and its subcomponents. The study sample size was 83 people, made up mostly of single Caucasian males at three separate residential facilities.

A significant association was revealed between social support and TQOL in patients with mental illness at residential facilities. Furthermore, the study showed positive associations between the different QOL subcomponents, SQOL and OQOL areas, and total social support and its three subcomponents. The results presented here reinforce previous findings on the importance of social support to quality of life for patients with mental illness (Mares et al, 2002; Goldberg et al, 2003; Nelson el al, 1995). This study also showed a novel association between total social support and the QOL subcomponents of QOLF and QOLSH.  Other novel features of the study were an examination of the relationship between support from friends and QOLH, as well as an exploration of the relationship between support from a significant other and QOLM. The results presented here suggest that age, gender, facility location, funding, length of stay and marital status may all be significantly predictive of QOL in residential home clients.
As shown in table 3, residential home clients had high TQOL. Out of a possible 224 points on the QOL questionnaire instrument, the patients’ mean score was 160 points (72% of the possible points), suggesting a moderate to high self-reported level of QOL. The high QOL could be attributed in part to the quality of mental health services and housing that the patients received. Mental health services and housing were found to be significant predictors of TQOL score.

Multivariate analyses of the data revealed that total social support was related to QOLSH and QOLF. The increased levels of total social support with regards to increased levels of self and home maintenance and finance could indicate that patients put more effort in caring for their personal living spaces and participating in the general care of the residential facility and were more optimistic about their future finances.

Social support from friends was significantly and positively related to QOLF and was almost a significant predictor of QOLH. There was a special significance for social support from friends for most of the study participants. Almost all of the psychiatric patients reported having some form of friendship with other psychiatric patients. Due in part to the enduring nature of their mental illness, most patients did not report having regular contact with their family members; moreover, most did not maintain regular relationships with a significant other. Of the subcomponents of Social Support, it would therefore be logical to conclude from these results that social support from friends exerted the strongest influence on overall social support in our sample of residential home clients.

Social support from a significant other was only significantly and positively related to QOLM. Social support from family only tended towards a positive relationship with self and home maintenance QOLSH.

Age was not related to TQOL but was positively related to QOLF and negatively related to QOLE. In addition the multivariate test revealed that age was significantly related to QOLU.

In examining the role of gender, we found that female clients received more social support from their families as well as higher QOLSH than male clients (bivariate analyses of data not shown here).  However, it should be noted that only 21.7% of the study participants were women, and all female clients were located at location 3. Females may ascribe a higher level of importance to self and home maintenance than do men, which could in principle account for the higher mean QOLSH in female clients than in male clients.  Female clients may also have felt a greater stake in contributing to both their personal areas and that of the facility, as compared to male clients.  

Length of stay was significantly related to TQOL and QOLH. In addition the multivariate analyses revealed that length of stay was significantly related to QOLE, QOLH and QOLTR. These findings suggest that psychiatric patients who stayed for longer periods of time at the residential facilities were more likely to acclimate to their surroundings, reporting increased levels of satisfaction with both their housing and their quality of life. Patients who stayed for longer periods of time at the residential homes were also more likely to seek employment and transportation services, when compared to their counterparts with shorter length of stay.

The type of patient funding, whether Medicare or Medicaid, was influential upon QOLE and QOLT. Medicaid patients scored higher on QOLE but lower on QOLT as compared to those on Medicare.  Medicaid funded 80.7% of the patients in our sample.

No significant relationship was found between marital status and TQOL. However, when examining the subcomponents of QOL, divorced clients had significantly lower QOLPH than single clients.  Married clients had significantly lower QOLF and QOLU as compared to single clients. It should be noted that out of the 83 patients in the study, only five patients were married and nine were divorced.

These findings about the role of marital status on quality of life were somewhat unanticipated.  Indeed, the results of previous investigations  (see for example, Chand et al., 2004; and Lang et al., 2002) suggested a strong positive role of being married  as a predictor of overall life satisfaction (in addition to age and higher income).  The small number of married participants (5 married patients) in the study could explain this discrepancy. Also, another possible explanation for the lower score for both married and divorced patients regarding the issue of finance, completing tasks and use of time could be related to comparisons of their current activities, or lack thereof, to their former lives.

Reported Quality of Life in subjects varied significantly from one residential home to another.  There was a relationship between residence location and QOL with location 1 scoring higher on various QOL components than location 3, while location 2 scored higher on QOLF than location 3. There were notable differences between the three locations with respect to both the gender of patients sampled, and the total number of patients. For example, Location 3 was the only location at which both men and women were housed, and it contained the largest group size.  Locations 1 and 2 were similar in design, and both housed an all-male population. Here we speculate briefly as to the reasons why clients at Locations 1 and 2 reported having higher quality of life than clients at location 3.  First, the larger number of patients in the home at location 3 suggests that crowding may have some role in reported quality of life; however, we did not measure this factor directly.  Secondly, the mixture of men and women at Location 3 suggests that male/female interactions may not be beneficial.  Finally, Location 3 was located in a separate geographic location from the other two homes that we sampled.  Thus, the geographic location itself may have been less favorable to clients at Location 3.   

The results of multivariate analyses demonstrate that total social support was positively associated with both the objective and subjective domains of QOL. Social support from friends was also significantly related to both objective and subjective QOL. We found that the lower level of reported quality of life in patients who lacked social support was explainable, at least to some extent, by a low level of connection to family members. Further, many of the patients with low reported QOL were unable to sustain a relationship with a significant other.  The lack of connectedness to family and significant others suggest that mental patients rely heavily instead upon social support from friends, which affords them higher quality of life.  

Previous research (see for example, Bussbach and Wiersma, 2002) suggested that affective bias, poor insight, lack of adaptive processes and persistently unfavorable life circumstances may all influence subjective measurements of subjective quality of life. Further, perceived QOL implies a subjective judgment about satisfaction that can be affected by many variables.  It would thus be reasonable to expect a positive relationship between satisfaction with social support and QOL (Caron, Tempier, Mercier, & Leouffre 1998). Previous research by Tempier et al. 1998 suggested that subjective QOL in patients with SMI tended to be lower for welfare recipients than for patients with SMI who were not on welfare

Our findings on the impact of social support upon subjective QOL are thus consistent with those of previous research (see for example, Lam & Rosenheck, 2000).  It is our hope that by carrying out our study, the clients accrued some benefits.  Indeed, focusing upon a person’s subjective view of his or her QOL may be important in terms of empowering that person, and in strengthening his or her involvement and participation in the rehabilitative process (Lustig, Crowder, 2000).

Total SS was significantly related to total QOL. Of the nine subcomponents of QOL, only two domains (self and home maintenance, and financial services and concerns) were related to total social support.

SS from friends was significantly related to the QOL subcomponent of housing, was close to significance as a positive predictor of the QOL subcomponent of finance, and was also significantly related to both objective and subjective QOL.

Perhaps the most significant finding reported here is that social support from friends has a strong positive impact upon QOL in residential home clients with SMI.  For most of the patients, social contact with friends was the most significant source of interaction in their lives.  The clients evidently relied more heavily upon that connection than they did a family member or a significant other as a source of social support.  This highlighted role of social support from friends is plainly evident upon examination of the social network for many psychiatric patients in residential homes- reduced connection to family members and an inability to sustain a relationship with a significant other.   

Study limitations
Here, we briefly discuss the limitations to our approach.  First, many of the items on the QOL questionnaire pertain to the type of services received and satisfaction with the services received by the residential psychiatric patients.  Thus, some of these items cannot be largely affected by social support from friends, family or a significant other. In the multivariate analyses the R2 value was 0.3, or 30% of the variance. In other words, the model did not explain about 70% of the concerns regarding QOL.  Areas for further exploration of these influential factors to QOL include measurement of patients’ emotions and feelings regarding their specific living situation, and an assessment of the impact of different therapeutic approaches upon mental health treatments.  Additionally, factors external to the current lives of patients at the residential facility are perhaps worthy of further exploration for their impact upon QOL.

Second, the instrument that we used to measure QOL did not fully completely assess transportation, finance, or the physical health of the patient. Patients have varied needs, some requiring transportation and financial services while other patients do not; these issues were explored only superficially in our study. We also did not directly measure the direct impact of variations in psychiatric medications prescribed to the patients, type of care received for those with chronic illness, nor the overall impact of chronic illness upon daily life.

Thirdly, some of the personal information that we gathered on patients was not independently verifiable, and could have been influenced by bias.  In order to ensure patient confidentiality, we did not seek access to medical records or other documentation required to verify patients’ responses to questionnaire items.  Lastly, non-normal distribution of the QOL subcomponents and residuals may have affected the study results.

The results confirm the importance of social support to Quality of Life in patients with mental illness at residential home facilities.  The findings also suggest a prominent role of marital status, finance, self and home maintenance, and support from friends in this relationship of social support to quality of life.

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